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Here’s how we raised a Series B for our AI startup during a downturn

Raising a Series B is never easy, and it’s become exceptionally difficult in the last year as the venture spigot slowed to a trickle. But it’s a different story if you’re an AI startup, right? After all, VCs are throwing money at the AI space.

Not so fast.

Already, the headline-grabbing funding rounds for generative AI companies are beginning to slow, and with almost every startup calling itself an “AI company,” it will become more difficult for true AI startups to stand out.

For founders trying to raise a Series B for their AI startups in the next six to 12 months, a more challenging fundraising environment likely awaits.

So what can AI founders do to raise a Series B when AI is everywhere? As a founder who raised a $40 million Series B from top investors in August last year, I can share a few strategies that worked for us.

Convey the “why” behind AI

You may feel like your startup is all about AI, but is it really? Countless startups are looking for ways to incorporate AI into their products. There’s nothing wrong with adding AI features, but if that’s all you’re doing, then claiming to be an AI startup just for the sake of it will diminish your credibility.

For founders trying to raise a Series B for their AI startups in the next six to 12 months, a more challenging fundraising environment likely awaits.

If AI is essential to your solution, you should be prepared to explain the measurable impact it has on your product offering. Do your models generate a few points of improvement over the best available baseline, or does it represent a significant step-function leap from the status quo?

You can convey AI’s impact on your startup in several ways, including quantitative metrics like model performance, business value measures like return on investment (ROI) and total cost of ownership (TCO), and qualitative proof points like case studies and success stories.

But impact alone is not enough. OpenAI’s domination of the AI space poses a threat to countless startups, particularly those that act as wrappers to public models like GPT-4. In today’s hyper-competitive landscape, it’s important to articulate how your startup stands apart from major players.

For instance, what moats does your business have? Do you have a valuable, proprietary dataset? A unique business workflow? Domain expertise? These are all critical ways to communicate your startup’s competitive edge.

Establish ironclad credibility with investors

After being inundated with AI startups, investors have become savvier about identifying what is and what isn’t AI. With the accessibility of large language models (LLMs), building an “AI startup” has become much easier and cheaper.


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